基于GLM-PSO-coKriging模型的地表形变研究
Research on Surface Deformation Based on GLM-PSO-coKriging Model
查看参考文献49篇
|
文摘
|
以斜坡灾害易发地带兰州市城关区为研究区,通过PS-InSAR技术提取地表形变点的地表形变速率,反映地质灾害在空间范围内的分布.以协克里金插值为基础,结合广义线性模型(GLM)和粒子群优化算法(PSO),构建PSO-GLM-coKriging插值模型,以地表形变速率为主变量,DEM,岩土疏松度和NDVI拟合参数为协变量,进行空间插值模拟.与co-Kriging模型和GLM-co-Kriging模型相比较,PSO-GLM-coKriging插值模型具有更高的精度和更好的模拟效果,消除了多维度产生的复杂度,改善了小尺度范围内的插值效果,3个模型的误差分别为1.25 mm/year,0.70 mm/year,0.47 mm/year.因此,通过PSOGLM插值模型对形变点空白区的插值模拟,对城关区城镇化的规划建设提供一定的数据和理论支撑. |
|
其他语种文摘
|
Taking the Chengguan District of Lanzhou City as a research area in the slope disaster-prone area, the surface deformation rate of surface deformation points is extracted by PS- InSAR technology, and the deformation rate can effectively reflect the distribution and uplifting of geological disasters in the spatial range. Based on the coKriging interpolation, combined with the generalized linear model (GLM) and the particle swarm optimization (PSO) algorithm, the coKrigong interpolation is optimized by fitting the linear model to construct the PSO- GLM- coKriging interpolation model to the surface deformation rate. The main variables, DEM, geotechnical porosity and NDVI fitting parameters were covariates, and spatial interpolation simulations were performed. Compared with the co- Kriging model and the GLM-co- Kriging model, the PSO-GLM-coKriging interpolation model has higher precision and better simulation effect, eliminating the complexity of multidimensional generation and improving the small-scale range. Interpolation effect, the error of the three models is 1.25mm/year, 0.70mm/year, 0.47mm/year. By comparison, the PSO- GLM- coKriging interpolation model has higher simulation accuracy and better simulation results. In the overall range, the interpolation results of the three models are similar in spatial distribution, in line with the actual situation of the surface. Therefore, the interpolation simulation of the blank area of the deformation point is carried out by the PSO-GLM interpolation model to fill the gap that the PS- InSAR technology can not extract the surface information at the non- deformation point, and the ground subsidence and uplift with sudden degeneration and sudden landslides will be completed. Geological disasters have been effectively combined, and the coupling relationship between geological disasters with high uncertainty and the monitoring of surface deformation can be established, which provides certain data and theoretical support for the planning and construction of urbanization in Chengguan District. |
|
来源
|
地球信息科学学报
,2018,20(11):1579-1591 【核心库】
|
|
DOI
|
10.12082/dqxxkx.2018.180289
|
|
关键词
|
PS-InSAR技术
;
地质灾害
;
地表形变速率
;
协克里金插值
;
PSO-GLM-coKriging插值模型
|
|
地址
|
1.
北京林业大学, 精准林业北京市重点实验室, 北京, 100083
2.
秦皇岛市林业局, 秦皇岛, 066004
|
|
语种
|
中文 |
|
文献类型
|
研究性论文 |
|
ISSN
|
1560-8999 |
|
学科
|
测绘学;地质学 |
|
基金
|
中央级公益性科研院所基本科研业务费专项资金项目
;
国家“十二五”科技支撑计划项目
|
|
文献收藏号
|
CSCD:6374437
|
参考文献 共
49
共3页
|
|
1.
秦晓琼. 高分辨率PS-InSAR在轨道交通形变特征探测中的应用.
测绘学报,2016,45(6):713-721
|
CSCD被引
26
次
|
|
|
|
|
2.
Sousa J. PS-InSAR processing methodologies in the detection of field surface deformation-Study of the Granada basin (Central Betic Cordilleras, southern Spain).
Journal of Geodynamics,2010,49(3):181-189
|
CSCD被引
7
次
|
|
|
|
|
3.
Greif V. Monitoring of post-failure landslide deformation by the PS-InSAR technique at Lubietova in Central Slovakia.
Environmental Earth Sciences,2012,66(6):1585-1595
|
CSCD被引
3
次
|
|
|
|
|
4.
屈春燕. 基于PSInSAR技术的海原断裂带地壳形变初步研究.
地球物理学报,2011,54(4):984-993
|
CSCD被引
19
次
|
|
|
|
|
5.
张学东. 多轨道集成PS-InSAR 监测高速公路沿线地面沉降研究———以京沪高速公路(北京—河北)为例.
测绘通报,2014(10):67-69
|
CSCD被引
11
次
|
|
|
|
|
6.
周朝栋. 基于PS-InSAR和GIS的北京平原区建筑荷载对地面沉降的影响.
地球信息科学学报,2016,18(11):1551-1562
|
CSCD被引
8
次
|
|
|
|
|
7.
熊思婷. 邻轨PS-InSAR地面沉降结果拼接处理方法与实验.
地球信息科学学报,2014,16(5):797-805
|
CSCD被引
5
次
|
|
|
|
|
8.
张志斌. 兰州市回族人口空间演化及其社会响应.
地理科学,2014,34(8):921-929
|
CSCD被引
4
次
|
|
|
|
|
9.
方苗. 基于GIS和Logistic回归模型的兰州市滑坡灾害敏感性区划研究.
遥感技术与应用,2011,26(6):845-854
|
CSCD被引
18
次
|
|
|
|
|
10.
马欢. 基于数据同化的地下水埋深插值研究.
农业机械学报,2017,48(4):206-214
|
CSCD被引
9
次
|
|
|
|
|
11.
李树生.
基于广义线性模型的森林植物多样性估测的研究,2008
|
CSCD被引
2
次
|
|
|
|
|
12.
朱昳橙. 怒江州滑坡地质灾害气象预警模型研究.
云南大学学报:自然科学版,2016,38(4):610-619
|
CSCD被引
5
次
|
|
|
|
|
13.
黄玉洁.
自然灾害风险模型分析,2015
|
CSCD被引
1
次
|
|
|
|
|
14.
Ciampalini A. The effectiveness of high-resolution LiDAR data combined with PSIn-SAR data in landslide study.
Landslides,2016,13(2):399-410
|
CSCD被引
6
次
|
|
|
|
|
15.
Ciampalini A. Landslide susceptibility map refinement using PSInSAR data.
Remote Sensing of Environment,2016,184:302-315
|
CSCD被引
8
次
|
|
|
|
|
16.
Fokker P A. Application of an ensemble smoother with multiple data assimilation to the Bergermeer gas field, using PS-InSAR.
Geomechanics for Energy & the Environment,2016,5:16-28
|
CSCD被引
1
次
|
|
|
|
|
17.
Qin X. Exploring temporal-spatial characteristics of Shanghai road networks settlement with multi-temporal PSInSAR technique.
Geomatics&Information Science ofWuhan University,2017,42(2):170-177
|
CSCD被引
1
次
|
|
|
|
|
18.
Chen F. Surface motion and structural instability monitoring of Ming Dynasty city walls by two-step Tomo-PSInSAR approach in Nanjing city, China.
Remote Sensing,2017,9(4):371
|
CSCD被引
3
次
|
|
|
|
|
19.
Bayer B. The influence of external digital elevation models on PS-InSAR and SBAS results: Implications for the analysis of deformation signals caused by slow moving landslides in the Northern Apennines (Italy).
IEEE Transactions on Geoscience & Remote Sensing,2017,99:1-14
|
CSCD被引
1
次
|
|
|
|
|
20.
张永红. 基于SAR干涉点目标分析技术的城市地表形变监测.
测绘学报,2009,38(6):482-487
|
CSCD被引
32
次
|
|
|
|
|
了解气象卫星更多信息，请访问